Data Engineer

Minimum 5+ years working experience as a data or software engineer in a fast-paced growing company. Excellent SQL and Python knowledge strong hands-on data modeling and data warehousing skills and experience in transformations orchestrated through technologies such as dbt/cloud data flow would be a plus. Strong experience applying software engineering best practices to analytics (e.g. version control, testing, and CI/CD)

Must have Skills:

• Technical Proficiency:

  Possess excellent SQL and Python skills, with hands-on experience in data modeling and data warehousing. Knowledge of technologies like dbt/cloud dataflow is a plus.

• Best Practices:

  Strong experience applying software engineering best practices to analytics, including version control, testing, and CI/CD.

• Cloud Expertise:

  Power-user and expert in building scalable data warehouses and pipelines using cloud tools such as Snowflake, AWS, Google Cloud, and Cloud ETL tools like Databricks (Spark/Azure).

• ETL/ELT:

  Solid experience with ETL/ELT processes, scheduling tools (e.g., Talend, Airflow), and API management tools.

• Data Familiarity:

  Experienced with customer, marketing, and/or web data sources (e.g., Salesforce, Google Analytics, Ad Words, YouTube).

• Visualization:

  Proficient with data visualization tools and packages such as Looker, Tableau, and matplotlib.

• Attention to Detail:

  Strong attention to detail to identify and address data quality issues.

• Traits:

  You re a self-starter, motivated, responsible, innovative, and technology-driven individual who excels both independently and as part of a team.

• Communication:

  A proactive problem solver with excellent communication and project management skills, able to convey findings and solutions to technical and non-technical audiences.

Key Responsibilities:

• Requirements Gathering:

  Work closely with data users to understand business requirements.

• Data Modeling:

  Design high-performance, reusable, and scalable data models for our data warehouse to ensure consistent and reliable answers for end-users.

• Data Transformations:

  Write complex yet optimized data transformations in SQL/Python using dbt or similar technology.

• Data Management:

  Continuously discover, transform, test, deploy, and document data sources.